code: def conformer_rnnt_biasing_base(charlist=None, biasing=True) -> RNNT:
      r"""Builds basic version of Conformer RNN-T model with TCPGen.
  
      Returns:
          RNNT:
              Conformer RNN-T model with TCPGen-based biasing support.
      """
      return conformer_rnnt_biasing(
          input_dim=80,
          encoding_dim=576,
          time_reduction_stride=4,
          conformer_input_dim=144,
          conformer_ffn_dim=576,
          conformer_num_layers=16,
          conformer_num_heads=4,
          conformer_depthwise_conv_kernel_size=31,
          conformer_dropout=0.1,
          num_symbols=601,
          symbol_embedding_dim=256,
          num_lstm_layers=1,
          lstm_hidden_dim=320,
          lstm_layer_norm=True,
          lstm_layer_norm_epsilon=1e-5,
          lstm_dropout=0.3,
          joiner_activation="tanh",
          attndim=256,
          biasing=biasing,
          charlist=charlist,
          deepbiasing=True,
          tcpsche=30,
          DBaverage=False,
      )
  
imports: import math
  from typing import Dict, List, Optional, Tuple
  import torch
  from torchaudio.models import Conformer, RNNT
  from torchaudio.models.rnnt import _Joiner, _Predictor, _TimeReduction, _Transcriber
label_desc: Use image node_id 4 for calling a global function with example usage: conformer_rnnt_biasing_base(charlist, biasing) and returns: conformer_rnnt_biasing